Model

I used a linear regression model to predict the number of wildfire incidents based on several environmental factors. The outcome variable in our model is the count of wildfire incidents, which we aim to predict using continuous variables related to weather conditions. Specifically, the model includes predictors such as temperature, precipitation, humidity, and wind speed. The analysis revealed that higher temperatures and wind speeds are associated with an increase in wildfire incidents, while higher precipitation and humidity tend to reduce the likelihood of wildfires. This model provides insights into how changes in environmental conditions can impact the frequency of wildfires, helping to inform prevention and response strategies.


Call:
lm(formula = Incidents ~ Average_Temperature + Average_Precip + 
    Average_AvgRelHum + Average_AvgWindSpeed, data = trainData)

Residuals:
    Min      1Q  Median      3Q     Max 
-16.906  -8.097  -2.853   7.179  25.787 

Coefficients:
                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)          -19.4597    77.8368  -0.250 0.807190    
Average_Temperature    2.7701     0.5727   4.837 0.000522 ***
Average_Precip       485.3668   191.5574   2.534 0.027785 *  
Average_AvgRelHum     -2.9807     1.2273  -2.429 0.033495 *  
Average_AvgWindSpeed   8.2916     9.1085   0.910 0.382172    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 13.61 on 11 degrees of freedom
Multiple R-squared:  0.8308,    Adjusted R-squared:  0.7692 
F-statistic:  13.5 on 4 and 11 DF,  p-value: 0.000318
      RMSE   Rsquared        MAE 
16.0536332  0.7154655 14.0474810

Characteristic

Beta

95% CI

1

p-value
Average_Temperature 2.8 1.5, 4.0 <0.001
Average_Precip 485 64, 907 0.028
Average_AvgRelHum -3.0 -5.7, -0.28 0.033
Average_AvgWindSpeed 8.3 -12, 28 0.4
1

CI = Confidence Interval

Display the mathematical representation using LaTeX:

\(Y = \beta_0 + \beta_1 \times \text{Temperature} + \beta_2 \times \text{Precipitation} + \beta_3 \times \text{Humidity} + \beta_4 \times \text{Wind Speed} + \epsilon\)